No abstract

The Pantanal biome integrates the lowlands of the Upper Paraguay Basin (UPB), which is hydrologically connected to the biomes of the Cerrado and Amazon (the highlands of the UPB). The effects of recent land-cover and land-use (LCLU) changes in the highlands, combined with climate change, are still poorly understood in this region. Here, we investigate the effects of soil erosion in the Brazilian Pantanal under climate and LCLU changes by combining different scenarios of projected rainfall erosivity and land-cover management. We compute the average annual soil erosion for the baseline (2012) and projected scenarios for 2020, 2035, and 2050. For the worst scenario, we noted an increase in soil loss of up to 100% from 2012 to 2050, associated with cropland expansion in some parts of the highlands. Furthermore, for the same period, our results indicated an increase of 20 to 40% in soil loss in parts of the Pantanal biome, which was associated with farmland increase (mainly for livestock) in the lowlands. Therefore, to ensure water, food, energy, and ecosystem service security over the next decades in the whole UPB, robust and comprehensive planning measures need to be developed, especially for the most impacted areas found in our study.

No abstract

Several Sediment Delivery Ratio (SDR) models have been used to estimate Sediment Yield (SY), mainly in data-scarce and ungauged basins, such as in many regions of Brazil. However, it is difficult to choose the most suitable SDR model, mainly because of the lack of investigations of this approach using observed data. Here, we investigated the performance of five widely used SDR models (SDREST) to estimate sediment yield values (SYEST ) based on observed data in a tropical watershed. We used observed sediment yield values (SY OBS) during September 2011 to July 2017 in three sub-basins of the Guariroba Basin, Midwestern Brazil. To estimate the average annual soil loss, we used the Revised Universal Soil Loss Equation. The SDROBS and SYOBS ranged from 5.56 to 10.54% and 940.76 to 5,400.32 t yr-1, respectively. The Williams and Berndt (1972) method presented the best performance, with a percent bias ranging from -2.34 to 3.30% in SRD estimation. Therefore, this model provided suitable SDR and SY estimates, and may be useful to estimate SY in other tropical data-scarce and ungauged basins.

No abstract